Simultaneous localization and mapping (“SLAM”) is a technique that addresses the computational problem of simultaneously mapping an environment while localizing with respect to the map. For example, SLAM can be used in robotics so that a robot can generate a map of a facility for the purposes of navigation while continuously orienting itself with respect to the map. Applications for SLAM are widespread. SLAM can be used in facilities such as hospitals, warehouses, manufacturing and industrial facilities, retail locations, etc.
Known SLAM techniques require that an entire facility be traversed (e.g. by a robot) in order to generate a map of the facility. For large facilities, traversing the entire facility in order to generate a map can be an onerous task. In some cases, it may be necessary to obtain a map of the entire facility, or substantial portions thereof, before a robot can be used to perform other functions in the facility.
Some solutions have been proposed for providing a map without the requirement for traversing an entire facility or environment. For example, an electronic map for use in automobile navigation may be generated based on images of the Earth captured by a satellite. In another example, an electronic map for use by vehicles in an indoor industrial facility may be generated based on a schematic of the facility. However, in these cases, a new set of satellite images or a new schematic of the facility are required in order to update the map to reflect any changes in the environment or facility.